Traffic Congestion Resolution and Driving Assistance System and Method

• US 20130041574A1
• Filed: 08/10/2012
• Published: 02/14/2013
• Est. Priority Date: 08/11/2011
• Status: Active Grant

• Current Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Original Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Inventors: KOSHIZEN, TAKAMASA
• Granted Patent: US 8,762,039 B2
• Time in Patent Office: Days
• US Class Current: 701/118
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station

Abstract

A traffic congestion resolution and driving assistance system and method include obtaining the acceleration of a vehicle; calculating a power spectrum corresponding to frequencies from the acceleration; calculating a simple regression line of the power spectrum, and calculating the maximum value of the amount of change in the slope of the simple regression line. The system and method also include detecting the intervehicular distance between the vehicle and a preceding vehicle; estimating the intervehicular distance distribution from the detected intervehicular distance using a distribution estimating method; and calculating the minimum value of the covariance from the estimated intervehicular distance distribution. The system and method further include estimating the vehicle group distribution in front of the vehicle from the correlation between the minimum value of the covariance and the maximum value of the slope; performing a real-time traffic congestion prediction; and delivering real-time traffic congestion prediction information to the vehicle.

Claims

1. A server-based traffic congestion resolution and driving assistance method comprising the steps of:

obtaining an acceleration of a vehicle that is subject to information delivery;

calculating a power spectrum corresponding to frequencies from frequency analysis of the obtained acceleration;

calculating a simple regression line of the calculated power spectrum, and calculating a maximum value of an amount of change in a slope of the simple regression line within a predetermined frequency range as a maximum value of the slope;

detecting an intervehicular distance between the vehicle and a preceding vehicle;

estimating an intervehicular distance distribution from the detected intervehicular distance using a distribution estimating method;

calculating a minimum value of a covariance from the estimated intervehicular distance distribution;

estimating a vehicle group distribution in front of the vehicle from a correlation between the minimum value of the covariance and the maximum value of the slope;

performing a real-time traffic congestion prediction based on the estimated vehicle group distribution; and

delivering real-time traffic congestion prediction information to the vehicle.

2. A server-based traffic congestion resolution and driving assistance method according to claim 1, wherein, in the step for obtaining the acceleration, the acceleration is calculated and obtained from a change over time in current position information transmitted by the vehicle or a change over time in speed information transmitted by the vehicle.

3. A server-based traffic congestion resolution and driving assistance method according to claim 1, wherein, in the step for delivering real-time traffic congestion prediction information, driving guidance information is created based on the real-time traffic congestion prediction information, and the driving guidance information including the real-time traffic congestion prediction information is delivered to the vehicle.

4. A server-based traffic congestion resolution and driving assistance method according to claim 1, wherein, in the step for delivering real-time traffic congestion prediction information, the real-time traffic congestion prediction information is delivered first to a vehicle highly impacted by traffic congestion formation in a vehicle group comprising a plurality of vehicles.

5. A traffic congestion resolution and driving assistance system, comprising:

an acceleration detector for determining an acceleration of a vehicle;

a frequency analyzer for calculating a power spectrum corresponding to frequencies from frequency analysis of the determined acceleration;

a simple regression calculator for calculating a simple regression line of the calculated power spectrum;

a slope maximum value calculator for calculating a maximum value of an amount of change in a slope of the simple regression line within a predetermined frequency range as a maximum value of the slope;

a preceding vehicle detector for detecting an intervehicular distance between the vehicle and a preceding vehicle;

an intervehicular distance distribution estimator for estimating the intervehicular distance distribution from the detected intervehicular distance using a distribution estimating method;

a covariance minimum value calculator for calculating a minimum value of a covariance from the estimated intervehicular distance distribution;

a correlation calculator for estimating a vehicle group distribution in front of the vehicle from a correlation between the calculated covariance minimum value and the calculated slope maximum value; and

a traffic congestion predictor for performing a real-time traffic congestion prediction based on the estimated vehicle group distribution and delivering real-time traffic congestion prediction information to the vehicle.

6. A traffic congestion resolution and driving assistance system according to claim 5, wherein driving guidance information is created based on the real-time traffic congestion prediction information, and the driving guidance information is delivered to the vehicle.

7. A traffic congestion resolution system according to claim 6, wherein the acceleration detector determines accelerations of a plurality of vehicles in a plurality of vehicle groups;

the preceding vehicle detector detects an intervehicular distance between each vehicle and a corresponding preceding vehicle; and

the real-time traffic congestion prediction information and the driving guidance information are delivered to vehicles in at least one vehicle group.

8. A traffic congestion resolution system according to claim 7, wherein the real-time traffic congestion prediction information and the driving guidance information are simultaneously provided to the vehicles.

9. A traffic congestion resolution system according to claim 7, wherein the real-time prediction information and the driving guidance information are provided to targeted vehicles in at least one vehicle group within a predetermined range predicted to impact each other in forming traffic congestion.

10. A traffic congestion resolution system according to claim 9, wherein the targeted vehicles include at least one vehicle group within a predetermined distance range predicted to form traffic congestion and a predetermined percentage of vehicles in the at least one vehicle group within the predetermined distance range.

11. A traffic congestion resolution system according to claim 5, wherein the correlation is a correlation map of the calculated covariance minimum value and the calculated slope maximum value.

12. A traffic congestion resolution system according to claim 11, wherein the traffic congestion predictor determines whether or not a boundary state or critical region exists in the correlation map;

and when a boundary state or critical region exists in the correlation map, driving guidance information is created based on the real-time traffic congestion prediction information and delivered to the vehicle.

13. A traffic congestion resolution system according to claim 11, wherein when a possibility of traffic congestion occurring is smaller than a first predetermined threshold value, there is no boundary state or critical region in the correlation map;

and when the possibility of traffic congestion occurring is higher than a second predetermined threshold value, there is a boundary state or critical region in the correlation map.

14. A traffic congestion resolution system according to claim 13, wherein the possibility of traffic congestion is determined by a prediction interval for traffic congestion, the prediction interval for traffic congestion being a parameter corresponding to the slope maximum value;

and wherein the parameter is larger when the possibility of traffic congestion occurring ahead of the vehicle in a direction of travel is high, and the parameter is smaller when the possibility of traffic congestion occurring ahead of the vehicle in the direction of travel is low.

15. A traffic congestion resolution system according to claim 14, wherein the traffic congestion predictor determines functions for values of predictive degrees of traffic congestion corresponding to slope maximum values, stores the functions in memory, and determines the prediction interval for traffic congestion relative to the calculated slope maximum value by referencing the stored functions.

16. A computer program product embodied on a computer-readable media, the media comprising computer-readable instructions, the instructions operable to cause one or more processors to perform operations comprising:

obtaining an acceleration of a vehicle;

calculating a power spectrum corresponding to frequencies from frequency analysis of the obtained acceleration;

calculating a simple regression line of the calculated power spectrum, and calculating a maximum value of an amount of change in a slope of the simple regression line within a predetermined frequency range as a maximum value of the slope;

detecting an intervehicular distance between the vehicle and a preceding vehicle;

estimating an intervehicular distance distribution from the detected intervehicular distance using a distribution estimating method;

calculating a minimum value of a covariance from the estimated intervehicular distance distribution;

estimating a vehicle group distribution in front of the vehicle from a correlation between the minimum value of the covariance and the maximum value of the slope;

performing a real-time traffic congestion prediction based on the estimated vehicle group distribution; and

delivering real-time traffic congestion prediction information to the vehicle.

17. A computer program product according to claim 16, wherein the real-time traffic congestion prediction information indicates that a possibility of traffic congestion occurring is higher than a predetermined threshold value;

and when the real-time congestion prediction information is delivered to the vehicle, at least one notification operation is performed by a vehicle processor to indicate the possibility of traffic congestion occurring.

18. A computer program product according to claim 17, wherein the at least one notification operation includes varying a color or gauge on a display, turning an indicator on or off, outputting a visual message, and outputting a sound or voice message.

19. A computer program product according to claim 16, further comprising transmitting the real-time congestion prediction information to a server device;

receiving driving guidance information, based on the real-time traffic congestion prediction information; and

delivering the driving guidance information to the vehicle.

20. A computer program product according to claim 19, wherein the driving guidance information includes at least one of information on target speed or target intervehicular distance for automatic drive control of the vehicle, and information on predetermined driving operations to refrain from accelerating or to increase the intervehicular distance relative to the preceding vehicle.